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An analytics approach to decision alternative prioritization for zero-emission zone logistics

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  • Deveci, Muhammet
  • Pamucar, Dragan
  • Gokasar, Ilgin
  • Delen, Dursun
  • Wu, Qun
  • Simic, Vladimir

Abstract

Urban freight transportation requires wise management considerations since it is one of the most challenging issues cities face to attain sustainability. To help with the challenging decision process, an integrated two-stage decision analysis approach is proposed. In the first stage, the Defining Interrelationships Between Ranked criteria (DIBR) method is used to consolidate the experts’ opinions to compute the weights of the predetermined decision criteria. In the second stage, a novel approach that integrates Combined Compromise Solution (CoCoSo) with the context of type-2 neutrosophic numbers is used to identify the most optimal management decision alternative. A case study is developed to show the viability and practicability of the proposed methodology. The results indicated that “building a logistics center (for fast and cheap delivery)” is the highest-ranked decision alternative, followed by “optimized and integrated operation of urban logistics,” and “zero-emission zone implementation,” respectively. The proposed methodology can be used as a decision analysis framework for urban city authorities while selecting the most optimal policies and related solution alternatives towards achieving and sustaining low-emission urban freight transportation.

Suggested Citation

  • Deveci, Muhammet & Pamucar, Dragan & Gokasar, Ilgin & Delen, Dursun & Wu, Qun & Simic, Vladimir, 2022. "An analytics approach to decision alternative prioritization for zero-emission zone logistics," Journal of Business Research, Elsevier, vol. 146(C), pages 554-570.
  • Handle: RePEc:eee:jbrese:v:146:y:2022:i:c:p:554-570
    DOI: 10.1016/j.jbusres.2022.03.059
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    References listed on IDEAS

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    Cited by:

    1. Kumar, Sourabh & Kumar Barua, Mukesh, 2022. "Modeling and investigating the interaction among risk factors of the sustainable petroleum supply chain," Resources Policy, Elsevier, vol. 79(C).

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